Optimization of Sensor Health Monitoring Algorithm Based on MAX30102

In order to meet people's needs for multifunctional and portable medical electronic devices at home, this paper proposes an algorithm for measuring multiple vital signs based on a single MAX30102 sensor. The MAX30102 photoelectric reflective sensor integrates photoelectric transmission and reception, digital-to-analog conversion, and data filtering, and has good anti-interference ability, system operation speed, and signal processing capabilities. This paper uses regression analysis technology to process temperature signals and effectively eliminates the error between body surface temperature and core temperature. The heart rate information is accurately extracted from the PPG signal by utilizing the pulse waveform data obtained by differential operation processing. In order to improve the accuracy of detection, the Dtrend detrending algorithm is selected to filter out baseline drift and motion artifact interference from the original signal to ensure the accuracy and stability of health vital sign data. The final experiment proves that the system has the characteristics of real-time, precision, and stability, which can meet the needs of real-time monitoring and has certain application value.